Biology subjects

Abdolalizadeh, A.

Publications and source records attributed to Abdolalizadeh, A..

4 recordsLinked to original sources

bioRxiv2026

Structural Connectivity Between the Locus Coeruleus and Nucleus Basalis of Meynert Relates to Dual-Task Performance

The noradrenergic locus coeruleus (LC) and the cholinergic nucleus basalis of Meynert (nBM) are key hubs of ascending neuromodulatory systems that shape large-scale brain dynamics. However, the behavioral relevance of the structural and functional connectivity between these nuclei remains poorly understood. Here, we investigated whether LC-nBM structural or functional connectivity is related to cognitive-motor dual-task performance in healthy younger and older adults. Fifty-four participants (36 older, 18 younger) underwent diffusion MRI, resting-state fMRI, and behavioral assessment using an MRI-compatible cognitive-motor dual-task paradigm. LC-nBM structural connectivity was estimated using tractography, whereas resting-state functional connectivity was quantified as Fisher z-transformed correlations between LC and nBM time series. LC-nBM structural connectivity was better explained by a quadratic rather than a linear or cubic age model, indicating non-linear age-related variation, whereas functional connectivity showed no significant age-related association. Higher LC-nBM structural connectivity was associated with greater cognitive dual-task cost, but not with motor dual-task cost or single- or dual-task reaction times. This association was not moderated by age group and was not statistically explained by attentional and executive performance as measured by the Test of Attentional Performance. These findings suggest that LC-nBM structural connectivity is selectively associated with cognitive-motor interference, potentially reflecting a neuromodulatory pathway that constrains the balance between task-specific stabilization and flexible cross-domain coordination during a cognitive-motor dual-tasking.

neuroscience↗

bioRxiv2025

Morphometric Latent Factors in Autism and Their Association with Receptor Profiles and Behavior

The profound heterogeneity of Autism Spectrum Disorder (ASD) is a major barrier to developing targeted therapies. While dimensional subtyping using functional connectivity (FC) has advanced the field, the intrinsic instability of FC limits its power to identify stable trait-like biomarkers. This study provides a direct comparison of latent factors derived from both FC and a stable morphometric measure, Morphometric Inverse Divergence (MIND), within the same ASD cohort. We hypothesized that stable structural factors would provide a more behaviorally relevant and biologically grounded account of ASD heterogeneity. Our findings reveal an important dissociation between functional and morphometric features. Latent factors derived from morphometric similarity (MIND) significantly correlated with core ASD behavioral traits (SCQ, SRS), while functional factors showed no association. This dissociation was also found at the neural level. Specifically, we observed weaker structure-function correspondence in the ASD group compared to the healthy control group (HC). Moreover, the stable structural factors were linked to trait-like neurodevelopmental mechanisms: the association with the CB1 receptor (important for synaptic pruning) observed in the HC was notably missing in the ASD group. Conversely, the functional factors were associated with a state-like arousal system (the norepinephrine transporter, NET). Collectively, our results demonstrate that stable morphometric-based factors, rather than time-varying functional ones, are predictive of behavioral traits in ASD. This work validates MIND as a robust approach and suggests that the link between structural organization and its neurodevelopmental (CB1) underpinnings is a more powerful and stable target for developing biomarkers in autism.

neuroscience↗

bioRxiv2025

Risky Choices After Frontal Brain Injury: Differential Effects in Self vs Other-Decision Contexts

Frontal lobe integrity is crucial for assessing risk and making informed decisions. This study investigated how frontal lobe lesions affect the computational mechanisms underlying risky choice, particularly when decisions impact oneself versus another person. A Patient Group of 20 individuals with frontal cortex damage and a Control Group of 20 matched individuals performed a gambling task, making accept/reject decisions on mixed-outcome gambles for themselves ("Self") or an anonymous other ("Other"). We provide a mechanistic account of choice behavior using Prospect Theory, the leading behavioral model of decision-making under risk, to quantify parameters for utility curvature, loss aversion, and probability weighting. Behaviorally, the Patient Group accepted significantly more disadvantageous gambles for themselves than did the Control Group yet showed a trend toward greater caution when choosing for others. Prospect Theory modeling revealed a specific computational phenotype for this behavior. Compared to the Control Group, the Patient Group exhibited significantly more pronounced utility curvature (lower , {beta}) and more linear, less distorted probability weighting (higher {gamma}). While patients also showed a trend toward lower loss aversion ({lambda}), this difference was not statistically significant. This combination of altered utility and probability processing explains their paradoxical risk-seeking. These findings suggest that frontal cortex damage disrupts the computation of subjective value, leading to a distinctive decision-making profile marked by altered utility curvature and reduced sensitivity to outcome magnitudes. This computational characterization deepens our understanding of frontal lobe contributions to decision-making and can inform targeted rehabilitation strategies.

neuroscience↗

bioRxiv2025

Domain-Specific Functional Network Adaptations Supporting Dual-Task Performance in Older Adults

Aging is associated with declines in both motor and cognitive functions, which are well captured by dual-task gait paradigms. However, the functional brain network mechanisms supporting motor and cognitive aspects of dual-task performance in aging remain unclear. We examined 40 older adults (50-80 years) and 20 younger adults (20-40 years) who performed a motor single-task (pedaling), a cognitive single-task (Go/NoGo), and a combined cognitive-motor dual-task during functional magnetic resonance Imaging (fMRI) using a custom-built MRI-compatible pedaling device. Behaviorally, older adults showed significant dual-task costs in motor performance, while cognitive performance was preserved. Neurally, older adults showed selective increases in connectivity within executive and motor-planning regions of cognitive networks, consistent with compensatory recruitment, whereas motor networks underwent broader reorganization, with strengthened frontoparietal control circuits but weakened cerebello-parietal and sensorimotor pathways. Multivariate analyses further revealed age-related differences in latent connectivity- behavior relationships: motor-network patterns in older adults were more dispersed, reflecting heterogeneous reorganization, whereas cognitive-network patterns were more overlapping across groups, suggesting relative preservation. These findings suggest that aging involves a domain-specific balance of resilience and vulnerability across brain networks and highlight motor-network adaption as a promising target for understanding why some older adults maintain function while others decline.

neuroscience↗